// Copyright (c) 2023 Huawei Technologies Co., Ltd
// Copyright (c) 2019, Facebook CORPORATION.
// All rights reserved.
//
// Licensed under the BSD 3-Clause License  (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// https://opensource.org/licenses/BSD-3-Clause
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

#include "op_plugin/AclOpsInterface.h"
#include "op_plugin/OpApiInterface.h"
#include "op_plugin/utils/op_api_common.h"

namespace op_api {
using npu_preparation = at_npu::native::OpPreparation;

at::Tensor bincount(const at::Tensor& self, const c10::optional<at::Tensor>& weight_opt, int64_t minlength) {
  DO_COMPATIBILITY(aclnnBincount, acl_op::bincount(self, weight_opt, minlength));
  // null tensor
  if (self.dim() == 1 && self.numel() == 0) {
    at::Tensor result;
    if (minlength <= 0) {
      result = npu_preparation::apply_tensor_without_format({0}, self.options().dtype(at::ScalarType::Long));
    } else {
      result = npu_preparation::apply_tensor_without_format({minlength}, self.options().dtype(at::ScalarType::Long));
      EXEC_NPU_CMD(aclnnBincount, self, weight_opt, minlength, result);
    }
    return result;
  }

  // cheack non-negative
  auto min_value = op_api::min(self).item().toLong();
  TORCH_CHECK(min_value >= 0, "bincount only support 1-d non-negative integral inputs.");

  // calculate output size
  auto sizes = op_api::max(self).item().toLong();
  sizes = (sizes < minlength) ? minlength : (sizes + 1);

  // weight convert dtype as same as output defined by torch
  at::Tensor result;
  if (!weight_opt.has_value()) {
    result = npu_preparation::apply_tensor_without_format({sizes}, self.options().dtype(at::ScalarType::Long));
  } else if (weight_opt->dtype() == at::ScalarType::Float) {
    result = npu_preparation::apply_tensor_without_format({sizes}, weight_opt->options().dtype(at::ScalarType::Float));
  } else {
    result = npu_preparation::apply_tensor_without_format({sizes}, weight_opt->options().dtype(at::ScalarType::Double));
  }

  EXEC_NPU_CMD(aclnnBincount, self, weight_opt, minlength, result);

  return result;
}
}  // namespace op_api
